Feature Selection Using Genetic Algorithms for the Generation of a Recognition and Classification of Children Activities Model Using Environmental Sound

In the area of recognition and classification of children activities, numerous works have been proposed that make use of different data sources. In most of them, sensors embedded in children’s garments are used. In this work, the use of environmental sound data is proposed to generate a recognition and classification of children activities model through automatic learning techniques, optimized for application on mobile devices. Initially, the use of a genetic algorithm for a feature selection is presented, reducing the original size of the dataset used, an important aspect when working with the limited resources of a mobile device. For the evaluation of this process, five different classification methods are applied, k-nearest neighbor (k-NN), nearest centroid (NC), artificial neural networks (ANNs), random forest (RF), and recursive partitioning trees (Rpart). Finally, a comparison of the models obtained, based on the accuracy, is performed, in order to identify the classification method that presents the best performance in the development of a model that allows the identification of children activity based on audio signals. According to the results, the best performance is presented by the five-feature model developed through RF, obtaining an accuracy of 0.92, which allows to conclude that it is possible to automatically classify children activity based on a reduced set of features with significant accuracy.In the area of recognition and classification of children activities, numerous works have been proposed that make use of different data sources. In most of them, sensors embedded in children’s garments are used. In this work, the use of environmental sound data is proposed to generate a recognition and classification of children activities model through automatic learning techniques, optimized for application on mobile devices. Initially, the use of a genetic algorithm for a feature selection is presented, reducing the original size of the dataset used, an important aspect when working with the limited resources of a mobile device. For the evaluation of this process, five different classification methods are applied, k-nearest neighbor (k-NN), nearest centroid (NC), artificial neural networks (ANNs), random forest (RF), and recursive partitioning trees (Rpart). Finally, a comparison of the models obtained, based on the accuracy, is performed, in order to identify the classification method that presents the best performance in the development of a model that allows the identification of children activity based on audio signals. According to the results, the best performance is presented by the five-feature model developed through RF, obtaining an accuracy of 0.92, which allows to conclude that it is possible to automatically classify children activity based on a reduced set of features with significant accuracy

Morphology Aspects of Hypothyroidism

Hypothyroidism is a common endocrine disorder resulting of low levels of thyroid circulating hormones. The prevalence in the general population varies between 0.3% and 3.7%. Presents as clinical or subclinical disease based on presence of symptoms and levels of serum TSH and free thyroxine and T4, respectively. Hypothyroidism has numerous etiologies, some of them are originated on the thyroid itself and some others are of extrathyroid origin, with variable manifestations. Classified as primary, secondary, tertiary and peripheral. Thyroid autoimmune disease is the principal cause. A new class of drugs against cancer, like the anti-CTLA-4 and anti-PD-L1/PD1 therapies have been associated with primary or secondary hypothyroidism. Endocrine disorders can be difficult to diagnose based only on morphological features because endocrine manifestations are caused primarily by a hormonal imbalance. Hypothyroidism may have a higher risk of morbidity and mortality. Finally, myxedematous coma is the main complication of terminal stages hypothyroidism

Estimation of Indoor Location Through Magnetic Field Data: An Approach Based On Convolutional Neural Networks

Estimation of indoor location represents an interesting research topic since it is a main contextual variable for location bases services (LBS), eHealth applications and commercial systems, among others. For instance, hospitals require location data of their employees, as well as the location of their patients to offer services based on these locations at the correct moments of their needs. Several approaches have been proposed to tackle this problem using different types of artificial or natural signals (ie, wifi, bluetooth, rfid, sound, movement, etc.). In this work, it is proposed the development of an indoor location estimator system, relying in the data provided by the magnetic field of the rooms, which has been demonstrated that is unique and quasi-stationary. For this purpose, it is analyzed the spectral evolution of the magnetic field data viewed as a bidimensional heatmap, avoiding temporal dependencies. A Fourier transform is applied to the bidimensional heatmap of the magnetic field data to feed a convolutional neural network (CNN) to generate a model to estimate the user’s location in a building. The evaluation of the CNN model to deploy an indoor location system (ILS) is done through measuring the Receiver Operating Characteristic (ROC) curve to observe the behavior in terms of sensitivity and specificity. Our experiments achieve a 0.99 Area Under the Curve (AUC) in the training data-set and a 0.74 in a total blind data set.Estimation of indoor location represents an interesting research topic since it is a main contextual variable for location bases services (LBS), eHealth applications and commercial systems, among others. For instance, hospitals require location data of their employees, as well as the location of their patients to offer services based on these locations at the correct moments of their needs. Several approaches have been proposed to tackle this problem using different types of artificial or natural signals (ie, wifi, bluetooth, rfid, sound, movement, etc.). In this work, it is proposed the development of an indoor location estimator system, relying in the data provided by the magnetic field of the rooms, which has been demonstrated that is unique and quasi-stationary. For this purpose, it is analyzed the spectral evolution of the magnetic field data viewed as a bidimensional heatmap, avoiding temporal dependencies. A Fourier transform is applied to the bidimensional heatmap of the magnetic field data to feed a convolutional neural network (CNN) to generate a model to estimate the user’s location in a building. The evaluation of the CNN model to deploy an indoor location system (ILS) is done through measuring the Receiver Operating Characteristic (ROC) curve to observe the behavior in terms of sensitivity and specificity. Our experiments achieve a 0.99 Area Under the Curve (AUC) in the training data-set and a 0.74 in a total blind data set

Pretreatment of vinasse from the sugar refinery industry under non-sterile conditions by Trametes versicolor in a fluidized bed bioreactor and its effect when coupled to an UASB reactor

During hydrous ethanol production from the sugar refinery industry in Mexico, vinasse is generated. Phenolic compounds and melanoidins contribute to its color and make degradation of the vinasse a difficult task. Although anaerobic digestion (AD) is feasible for vinasse treatment, the presence of recalcitrant compounds can be toxic or inhibitory for anaerobic microorganism. Therefore, this study presents new data on the coupled of the FBR (Fluidized Bed Bioreactor) to the UASB (Upflow Anaerobic Sludge Blanket) reactor under non-sterile conditions by T. versicolor. Nevertheless, for an industrial application, it is necessary to evaluate the performance in this kind of proposal system. Therefore, this study used a FBR for the removal of phenolic compounds (67%) and COD (38%) at non-sterile conditions. Continuous operation of the FBR was successfully for 26 days according to the literature. When the FBR was coupled to the UASB reactor, we obtained a better quality of effluent, furthermore methane content and yield were 74% and 0.18 m 3 CH/ kg COD respectively. This study demonstrated the possibility of using for an industrial application the coupled of the FBR to the UASB reactor under non-sterile conditions. Continuous operation of the FBR was carried out successfully for 26 days, which is the highest value found in the literature

Diseño de prototipo para mejorar la dicción mediante el uso de Modelos Ocultos de Markov

La comunicación oral en el ser humano es muy importante, sin embargo, la buena comunicación, independientemente del idioma, debe ser clara, objetiva y expresiva con el fin de que lo que se quiere expresar sea lo que el oyente entienda. El reconocimiento de voz, por otro lado, se basa en el estudio sobre el proceso del habla y la comunicación, y la forma en que este conocimiento puede ser aplicado como herramienta para diversas finalidades. El enfoque de esta investigación es el desarrollo de un prototipo didáctico para realizar pruebas de dicción en el idioma español. Para ello, se utilizaron 3 técnicas basadas en Modelos Ocultos de Markov (HMM) las cuales son Modelos Ocultos de Markov con DTW (MDTW), Modelos Ocultos de Markov con DTW aproximado por izquierda y derecha (MID) y Modelos Ocultos de Markov con relleno de palabras (MRP). Con esta estructura se logró distinguir entre calidades de dicción y con una eficiencia de reconocimiento por encima del 90 % para cualquiera de las técnicas utilizadas. Finalmente, con base en lo anterior, se programó una interfaz en Matlab la cual brinda resultados para la corrección de la dicción

Characterization of oncogene suppressor marker expression in patients with submucosal gastric carcinoma

The aim of the present study was to determine the clinical significance of p53 and p21ras p21wafl, p27kip1 and p16ink4a expression in cases of early gastric cancer. A total of 81 patients who had undergone gastrectomy with D2 lymphadenectomy between 1971 and 2004 were retrospectively investigated. The immunohistochemical expression of p21ras, p53, p21waf1/cip1, p27kip1 and p16ink4a in the tissues was evaluated. In normal, metaplastic and tumoral mucosa, p53 was positive in 53, 87.3, and 87.1% of the cases, respectively. In the same tissues, p21ras was positivE in 85.3, 86 and 96.8%, respectively. Positivity FOR p16ink4a was DETECTED IN 46.3, 91.1 and 86% OF THE CASES, respectively, WHEREAS p27kip1 WAS positiVE IN 60, 94.7 and 95.3%, and p21wafl/cip1 WAS positivE IN 32.4, 72.7 and 71.4% OF THE CASES, respectively. All THE tumors WERE positive for p53. Tumors with lymph node invasion presented WITH OVERexpression (+4) of p53 in 47% of the cases VS. 17% OF patients who DID not HAVE lymph node involvement. THEREFORE, higher expression of p53, p21ras and p21wafl/cip1 IN the tumor exhibited a statistically significant association with lymph node involvement.info:eu-repo/semantics/publishedVersio

Biomarker analysis of cetuximab plus oxaliplatin/leucovorin/5-fluorouracil in first-line metastatic gastric and oesophago-gastric junction cancer: results from a phase II trial of the Arbeitsgemeinschaft Internistische Onkologie (AIO)

<p>Abstract</p> <p>Background</p> <p>The activity of the epidermal growth factor receptor (EGFR)-directed monoclonal antibody cetuximab combined with oxaliplatin/leucovorin/5-fluorouracil (FUFOX) was assessed in first-line metastatic gastric and oesophago-gastric junction (OGJ) cancer in a prospective phase II study showing a promising objective tumour response rate of 65% and a low mutation frequency of <it>KRAS </it>(3%). The aim of the correlative tumour tissue studies was to investigate the relationship between <it>EGFR </it>gene copy numbers, activation of the EGFR pathway, expression and mutation of E-cadherin, V600E BRAF mutation and clinical outcome of patients with gastric and OGJ cancer treated with cetuximab combined with FUFOX.</p> <p>Methods</p> <p>Patients included in this correlative study (<it>n </it>= 39) were a subset of patients from the clinical phase II study. The association between <it>EGFR </it>gene copy number, activation of the EGFR pathway, abundance and mutation of E-cadherin which plays an important role in these disorders, BRAF mutation and clinical outcome of patients was studied. <it>EGFR </it>gene copy number was assessed by FISH. Expression of the phosphorylated forms of EGFR and its downstream effectors Akt and MAPK, in addition to E-cadherin was analysed by immunohistochemistry. The frequency of mutant V600E BRAF was evaluated by allele-specific PCR and the mutation profile of the E-cadherin gene <it>CDH1 </it>was examined by DHPLC followed by direct sequence analysis. Correlations with overall survival (OS), time to progression (TTP) and overall response rate (ORR) were assessed.</p> <p>Results</p> <p>Our study showed a significant association between increased <it>EGFR </it>gene copy number (≥ 4.0) and OS in gastric and OGJ cancer, indicating the possibility that patients may be selected for treatment on a genetic basis. Furthermore, a significant correlation was shown between activated EGFR and shorter TTP and ORR, but not between activated EGFR and OS. No V600E BRAF mutations were identified. On the other hand, an interesting trend between high E-cadherin expression levels and better OS was observed and two <it>CDH1 </it>exon 9 missense mutations (A408V and D402H) were detected.</p> <p>Conclusion</p> <p>Our finding that increased <it>EGFR </it>gene copy numbers, activated EGFR and the E-cadherin status are potentially interesting biomarkers needs to be confirmed in larger randomized clinical trials.</p> <p>Trial registration</p> <p>Multicentre clinical study with the European Clinical Trials Database number 2004-004024-12.</p

Uso y resultados del astegolimab en el manejo del asma severa: ¿qué se conoce?

Asthma is a chronic inflammatory disease of the respiratory tract which causes high health costs, substantially affects the quality of life and, depending on certain associated risk factors, reduces the functional capacity of the sufferer. By 2019, asthma affected 262 million people (4.3 % of the world’s population) and caused 461,000 deaths. It is estimated that therewill be an additional 100 million people with asthma by 2025. Severe asthma is a phenotype resistant to corticosteroids which causes a greater number of exacerbations and substantially affects the quality of life and functional capacity of the affected person. Its management was initially aimed at suppressing the symptoms and then evolved to understand, although not completely, the intrinsic systems of its generation. Thus, new ways of influencing its management have been studied by modulating the immune response and the inflammatory cascade with the generation of biological drugs. As a result of the study and identification of various endotypes and phenotypes, drugs with different mechanisms of action have been designed and have demonstrated to be considerably useful in recent years. However, there is evidence that resistance even to these drugs has occurred, being necessary to continue researching new therapeutic targets. Astegolimab is a novel human IgG2 monoclonal antibody that blocks IL-33 signaling by targeting ST2, its receptor, thus controlling the inflammatory response in severe asthma. A phase 2b clinical trial is currently undergoing, although previous results have found positive and significant results regarding immunomodulation, pulmonary function, symptomatology and quality of life. At present, there is almost no literature that has analyzed the potential of astegolimab in severe asthma, and practically only trials that have evaluated it and some reviews that have shared its pharmacokinetics and pharmacodynamics are available. Based on the above, the aim of this review is to synthesize evidence related to the results of the use of astegolimab insevere asthma and discuss epidemiological and pathophysiological aspects that highlight the need for the development of a safe, effective and efficient drug.El asma es una enfermedad inflamatoria crónica de las vías respiratorias que acarrea elevados costos en salud, afecta sustancialmente la calidad de vida y, dependiendo de ciertos factores de riesgo asociados, disminuye la capacidad funcional de quien lo padece. Para el 2019, el asma afectó a 262 millones de personas (4,3 % de la población mundial) y causó 461 000 muertes. Se estima que habrá 100 millones de personas adicionales con asma para el año 2025. El asma severa es un fenotipo resistente a corticoides que ocasiona mayor número de exacerbaciones, afecta sustancialmente la calidad de vida y capacidad funcional del afectado. Su manejo inicialmente se encamina a suprimir los síntomas, y este ha ido evolucionando hasta la comprensión, aún no completa, de los sistemas intrínsecos de su generación, conlo cual se han estudiado nuevas formas de incidir en su manejo, mediante la modulación de la respuesta inmune y la cascada inflamatoria, con la generación de medicamentos biológicos. A raíz del estudio e identificación de endotipos y fenotipos variados, se han diseñado este tipo de medicamentos, con distintos mecanismos de acción, que han demostrado una utilidad sólida en los últimos años. No obstante, existe evidencia de que se ha encontrado resistencia incluso aestos medicamentos, por lo que ha sido necesario seguir investigando nuevas dianas terapéuticas. El astegolimab es un novedoso anticuerpo monoclonal Ig G2 humano que bloquea la señalización de IL-33 al dirigirse a ST2, su receptor, por consiguiente, controla la respuesta inflamatoria en el asma severa. Actualmente, se encuentra en realización de ensayoclínico fase 2b, aunque experimentaciones previas han encontrado resultados positivos y significativos respecto a la inmunomodulación, función pulmonar, sintomatología y calidad de vida. En la actualidad, casi no existe literatura que haya analizado el potencial del astegolimab en el asma grave, y están disponibles prácticamente solo los ensayos que lo han evaluado y algunas revisiones que han compartido su farmacocinética y farmacodinamia. Sobre la base de lo anterior, el objetivo de esta revisión consiste en sintetizar evidencia relacionada con los resultados del uso del astegolimab en asma severa, discutiendo aspectos epidemiológicos y fisiopatológicos que resalten la necesidad del desarrollo de un fármacoseguro, eficaz y eficiente

Analysis of cell cycle-related proteins in gastric intramucosal differentiated-type cancers based on mucin phenotypes: a novel hypothesis of early gastric carcinogenesis based on mucin phenotype

<p>Abstract</p> <p>Background</p> <p>Abnormalities of cell cycle regulators are common features in human cancers, and several of these factors are associated with the early development of gastric cancers. However, recent studies have shown that gastric cancer tumorigenesis was characterized by mucin expression. Thus, expression patterns of cell cycle-related proteins were investigated in the early phase of differentiated-type gastric cancers to ascertain any mechanistic relationships with mucin phenotypes.</p> <p>Methods</p> <p>Immunostaining for Cyclins D1, A, E, and p21, p27, p53 and β-catenin was used to examine impairments of the cell cycle in 190 gastric intramucosal differentiated-type cancers. Mucin phenotypes were determined by the expressions of MUC5AC, MUC6, MUC2 and CD10. A Ki-67 positive rate (PR) was also examined.</p> <p>Results</p> <p>Overexpressions of p53, cyclin D1 and cyclin A were significantly more frequent in a gastric phenotype than an intestinal phenotype. Cyclin A was overexpressed in a mixed phenotype compared with an intestinal phenotype, while p27 overexpression was more frequent in an intestinal phenotype than in a mixed phenotype. Reduction of p21 was a common feature of the gastric intramucosal differentiated-type cancers examined.</p> <p>Conclusions</p> <p>Our results suggest that the levels of some cell cycle regulators appear to be associated with mucin phenotypes of early gastric differentiated-type cancers.</p

Cetuximab plus oxaliplatin/leucovorin/5-fluorouracil in first-line metastatic gastric cancer: a phase II study of the Arbeitsgemeinschaft Internistische Onkologie (AIO)

BACKGROUND: Cetuximab enhances the efficacy of chemotherapy in several cancer types. This trial assessed the activity of cetuximab and chemotherapy in advanced gastric cancer. METHODS: Patients with previously untreated, metastatic, gastric cancer received cetuximab 400 mg m(-2) at first infusion followed by weekly infusions of 250 mg m(-2) combined with FUFOX (oxaliplatin 50 mg m(-2), 5-FU 2000 mg m(-2), and DL-folinic acid 200 mg m(-2) d1, 8, 15 and 22 qd36). The primary endpoint was tumour response. RESULTS: Overall, 52 patients were enrolled. The most common grade 3/4 toxicities were diarrhoea (33%), and skin toxicity (24%). Efficacy was evaluable in 46 patients who showed a response rate of 65% (CI 95%: 50-79%) including four complete responses. Time to progression (TTP) was 7.6 months (CI 95%: 5.0-10.1 months) and overall survival (OS) was 9.5 months (CI 95%: 7.9-11.1 months). Epidermal growth factor receptor (EGFR) was detectable in 60% of tumours but showed no correlation with treatment outcome. A KRAS mutation was found in only 1 of 32 (3%) tumour samples analysed. CONCLUSION: Cetuximab plus FUFOX showed an interesting high response rate in metastatic gastric cancer. Cetuximab plus platinum-fluoropyrimidine chemotherapy is at present being investigated in a phase III randomised controlled trial